How to Control OpenClaw Cost (Part 1)

If you're building on OpenClaw, you've probably stared at a monthly bill and wondered where the money went. You're not alone. Most guides either repeat obvious tips or go deep on implementation details that take a team to ship.

This is a practical walkthrough. Two parts. Part 1 covers what to measure and how to fix routing and fallbacks.

What to measure first

You can't control what you don't measure. OpenClaw's dashboard gives call counts per model and total spend. That's not enough. You need at least:

• Cost per workflow – per month, per run, per user
• Token usage per step – and how much of that is repeated context
• Fallback volume and cost – how often, how much extra, what's triggering it
• Cost per user/feature – which parts of the product drive spend
• Error and retry volume – how many retries, what they cost, why they happen

Most teams see one monthly number. Without per-workflow and per-step data, you're guessing. A real-time cost tool that plugs into OpenClaw helps. Without it, you're flying blind.

Step 1: Optimize routing and fallbacks

The fastest way to cut OpenClaw costs is to fix routing and fallback rules. Often 30% or more, with small code changes.

Use the right model for the task

Teams often run everything on GPT-4o or Claude 3 Opus. These are great for complex reasoning. They're also 10–20x more expensive than smaller models for simple tasks.

A real estate client used GPT-4o for every step of lead qualification. $3,200/month. We moved 80% of the steps to GPT-4o Mini: classification, data extraction, initial responses. Kept GPT-4o for complex negotiation and custom recommendations. Bill dropped to $780. Same conversion, same quality.

Split your workflows into three tiers:

• High-stakes, complex – GPT-4o, Claude 3 Opus
• Mid-tier – GPT-3.5 Turbo, Claude 3 Sonnet
• Simple – GPT-4o Mini, Claude 3 Haiku, Llama 3 8B

Most tasks don't need the top tier. OpenClaw's routing rules can send each request to the right model automatically.

Fix fallback routing

Fallback is the biggest hidden leak for OpenClaw users. Failed calls often route to more expensive models. A few rules:

• Don't fall back to a pricier model by default. If GPT-4o fails, use something similar or cheaper.
• Cap fallback volume per hour, day, and workflow. A temporary rate limit shouldn't become a huge fallback bill.
• Investigate root cause. High fallback volume means something's wrong—fix limits, errors, or routing instead of ignoring it.

Optional: automatic model routing

Tools like ClawFirewall can analyze each request and route to the cheapest model that fits. OpenClaw gives you building blocks; full automation takes custom code or a dedicated tool.

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Part 2: Token waste, budget controls, and ongoing monitoring →